Results 11 to 20 of about 11,256,803 (209)
Can physics-informed neural networks beat the finite element method? [PDF]
IMA Journal of Applied Mathematics, 2023 Partial differential equations (PDEs) play a fundamental role in the mathematical modelling of many processes and systems in physical, biological and other sciences.
T. G. Grossmann +3 more
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Could an artificial-intelligence agent pass an introductory physics course? [PDF]
Physical Review Physics Education Research, 2023 Massive pre-trained language models have garnered attention and controversy due to their ability to generate human-like responses: attention due to their frequent indistinguishability from human-generated phraseology and narratives, and controversy due ...
G. Kortemeyer
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Respecting causality is all you need for training physics-informed neural networks [PDF]
arXiv.org, 2022 While the popularity of physics-informed neural networks (PINNs) is steadily rising, to this date PINNs have not been successful in simulating dynamical systems whose solution exhibits multi-scale, chaotic or turbulent behavior. In this work we attribute
Sifan Wang +2 more
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New horizons for fundamental physics with LISA [PDF]
Living Reviews in Relativity, 2022 The Laser Interferometer Space Antenna (LISA) has the potential to reveal wonders about the fundamental theory of nature at play in the extreme gravity regime, where the gravitational interaction is both strong and dynamical.
K. G. Arun +140 more
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Can ChatGPT support prospective teachers in physics task development? [PDF]
Physical Review Physics Education Research, 2023 The recent advancement of large language models presents numerous opportunities for teaching and learning. Despite widespread public debate regarding the use of large language models, empirical research on their opportunities and risks in education ...
S. Küchemann +6 more
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How understanding large language models can inform the use of ChatGPT in physics education [PDF]
European journal of physics, 2023 The paper aims to fulfil three main functions: (1) to serve as an introduction for the physics education community to the functioning of large language models (LLMs), (2) to present a series of illustrative examples demonstrating how prompt-engineering ...
Giulia Polverini, B. Gregorcic
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The standard model effective field theory at work [PDF]
Reviews of Modern Physics, 2023 The striking success of the Standard Model in explaining precision data and, at the same time, its lack of explanations for various fundamental phenomena, such as dark matter or the baryon asymmetry of the universe, suggests new physics at an energy ...
G. Isidori, Felix Wilsch, D. Wyler
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The death of the short-form physics essay in the coming AI revolution [PDF]
The Physical Educator, 2022 The latest AI language modules can produce original, high quality full short-form (300-word) Physics essays within seconds. These technologies such as ChatGPT and davinci-003 are freely available to anyone with an internet connection.
W. Yeadon +4 more
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Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications [PDF]
arXiv.org, 2022 Recent advances of data-driven machine learning have revolutionized fields like computer vision, reinforcement learning, and many scientific and engineering domains.
Zhongkai Hao +6 more
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Physics-informed dynamic mode decomposition
Proceedings of the Royal Society A, 2023 In this work, we demonstrate how physical principles—such as symmetries, invariances and conservation laws—can be integrated into the dynamic mode decomposition (DMD).
Peter J. Baddoo +4 more
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